Personalized Saliency in Task-Oriented Semantic Communications: Image Transmission and Performance Analysis

Kang, Jiawen; Du, Hongyang; Li, Zonghang; Xiong, Zehui; Ma, Shiyao; Niyato, Dusit; Li, Yuan

doi:10.1109/jsac.2022.3221990

Cited by 78 publications

(15 citation statements)

References 47 publications

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“…The authors of [21] propose an edge-sharing knowledge graph to enable semantic communication among intelligent devices in a network. In [22], the authors develop a communication system powered by a knowledge graph with subject-relation-object triples for transmission of images among unmanned aerial vehicles (UAVs).…”

Section: A Related Workmentioning

confidence: 99%

Engineering Semantic Communication: A Survey

Wheeler

Natarajan

2023

IEEE Access

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As the global demand for data has continued to rise exponentially, some have begun turning to the idea of semantic communication as a means of efficiently meeting this demand. Pushing beyond the boundaries of conventional communication systems, semantic communication focuses on the accurate recovery of the meaning conveyed from source to receiver, as opposed to the accurate recovery of transmitted symbols. In this survey, we aim to provide a comprehensive view of the history and current state of semantic communication and the techniques for engineering this higher level of communication. A survey of the current literature reveals four broad approaches to engineering semantic communication. We term the earliest of these approaches classical semantic information, which seeks to extend informationtheoretic results to include semantic information. A second approach makes use of knowledge graphs to achieve semantic communication, and a third utilizes the power of modern deep learning techniques to facilitate this communication. The fourth approach focuses on the significance of information, rather than its meaning, to achieve efficient, goal-oriented communication. We discuss each of these four approaches and their corresponding studies in detail, and provide some challenges and opportunities that pertain to each approach. Finally, we introduce a novel approach to semantic communication, which we term contextbased semantic communication. Inspired by the way in which humans naturally communicate with one another, this context-based approach provides a general, optimization-based design framework for semantic communication systems. Together, this survey provides a useful guide for the design and implementation of semantic communication systems.

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Section: A Related Workmentioning

confidence: 99%

Engineering Semantic Communication: A Survey

Wheeler

Natarajan

2023

IEEE Access

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“…The TDP P k is an important semantic metric for both Sem-Com and goal-oriented SemCom [262] and is defined as [262, eq. ( 17)]…”

Section: B Triplet Drop Probabilitymentioning

confidence: 99%

“…TDP is a generic semantic metric that is also a crucial performance analysis/optimization metric for wireless systems that are based on goal-oriented wireless SemCom [262]. It is defined in (53).…”

Section: ) Triplet Drop Probabilitymentioning

confidence: 99%

Making Sense of Meaning: A Survey on Metrics for Semantic and Goal-Oriented Communication

2023

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Semantic communication (SemCom) aims to convey the meaning behind a transmitted message by transmitting only semantically-relevant information. This semantic-centric design helps to minimize power usage, bandwidth consumption, and transmission delay. SemCom and goal-oriented SemCom (or effectiveness-level SemCom) are therefore promising enablers of 6G and developing rapidly. Despite the surge in their swift development, the design, analysis, optimization, and realization of robust and intelligent SemCom as well as goal-oriented SemCom are fraught with many fundamental challenges. One of the challenges is that the lack of unified/universal metrics of SemCom and goal-oriented SemCom can stifle research progress on their respective algorithmic, theoretical, and implementation frontiers. Consequently, this survey paper documents the existing metrics -scattered in many references -of wireless SemCom, optical SemCom, quantum SemCom, and goal-oriented wireless SemCom. By doing so, this paper aims to inspire the design, analysis, and optimization of a wide variety of SemCom and goal-oriented SemCom systems. This article also stimulates the development of unified/universal performance assessment metrics of SemCom and goal-oriented SemCom, as the existing metrics are purely statistical and hardly applicable to reasoning-type tasks that constitute the heart of 6G and beyond.

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“…The task splitting strategy is dynamically determined rather than using a fixed assignment. It depends on real-time channel conditions, the association between users and RSUs, variational task requirements (data volume and computational density), and available bandwidth and computing resource capacity [37]. In addition to these factors, the handoff issue of the edge network is also considered by adjusting the data splitting ratios in a flexible manner so that the task portion computed at the RSU is not interrupted by a handoff.…”

Section: A System Modelmentioning

confidence: 99%

High Altitude Platform Station (HAPS) Assisted Computing for Intelligent Transportation Systems

Ren

Abbasi

Kurt³

et al. 2021

2021 IEEE Global Communications Conference (GLOBECOM)

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Distributed computing enables Internet of vehicle (IoV) services by collaboratively utilizing the computing resources from the network edge and the vehicles. However, the computing interruption issue caused by frequent edge network handoffs, and a severe shortage of computing resources are two problems in providing IoV services. High altitude platform station (HAPS) computing can be a promising addition to existing distributed computing frameworks because of its wide coverage and strong computational capabilities. In this regard, this paper proposes an adaptive scheme in a new distributed computing framework that involves HAPS computing to deal with the two problems of the IoV. Based on the diverse demands of vehicles, network dynamics, and the time-sensitivity of handoffs, the proposed scheme flexibly divides each task into three parts and assigns them to the vehicle, roadside units (RSUs), and a HAPS to perform synchronous computing. The scheme also constrains the computing of tasks at RSUs such that they are completed before handoffs to avoid the risk of computing interruptions. On this basis, we formulate a delay minimization problem that considers task-splitting ratio, transmit power, bandwidth allocation, and computing resource allocation. To solve the problem, variable replacement and successive convex approximation-based method are proposed. The simulation results show that this scheme not only avoids the negative effects caused by handoffs in a flexible manner, it also takes delay performance into account and maintains the delay stability.Index Terms-Internet of vehicles (IoV), High altitude platform station (HAPS), distributed computing, edge network handoff.

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Personalized Saliency in Task-Oriented Semantic Communications: Image Transmission and Performance Analysis

Cited by 78 publications

References 47 publications

Engineering Semantic Communication: A Survey

Engineering Semantic Communication: A Survey

Making Sense of Meaning: A Survey on Metrics for Semantic and Goal-Oriented Communication

High Altitude Platform Station (HAPS) Assisted Computing for Intelligent Transportation Systems

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